Collective Data Stewardship
“DoD must assign Data Stewards, Data Custodians, and a set of functional Data Managers to achieve accountability throughout the entire data lifecycle.”
What is collective data stewardship?
col·lec·tive – /kəˈlektiv/ | Done by people acting as a group. | “a collective protest”
The essence of this guiding principle is that decisions about data need to be made and/or influenced by the people that are closest to the data. Why is this? Because these are the people that know the data best. No one person at the top or central team/panel of folks is going to get it right for the enterprise. Clearly, managing the data life cycle requires that you understand the data. (more on this later)
Establishing a team of data stewards, data custodians, and data managers ensures that data is being cared for and handled appropriately as it moves through the life cycle. These expert curators of the data need automation tools to help them view, organize, and manage their respective data domains. To this end, organizations are implementing solutions such as:
These technologies satisfy many of the data management needs, but hang on, the stated principle also mentions the concept of ‘achieving accountability’ throughout the data lifecycle. No steward, custodian, or manager wants to be held accountable for data that is not theirs. Similarly, none of these data managers want to be left in the dark as to the whereabouts of their data that is not represented in the data catalog. What’s needed is a solution that can add the following to the mix:
- Automated data discovery across all data types and sources
- e.g. cloud, on-premises, structured, unstructured, enterprise apps, data pipelines, source code repositories, ticketing systems, mainframes, CMDBs, big data, etc.
- Automated ML-based advanced data classification (minimal false positives = actionable results)
- Automated data sensitivity and business tagging / labeling
- Enterprise-wide metadata registry
To do their job well, data managers need comprehensive visibility to their data, not just the data that has been corralled into the catalog. They need to know where sensitive data elements reside and understand the sensitivity levels of all their data. Data types, data categories, data tags/labels, semantic domains, and corporate taxonomies all need to be established in order to fully understand the data.
BigID closes all these gaps and, in addition, provides two-way integration with today’s leading data catalogs to extend data coverage to more systems and enrich the catalog with data sensitivity tags, etc. BigID’s enterprise metadata registry that fits snugly into a data fabric/mesh architecture in order to provide greater data transparency and insights.
BigID helps agencies understand their data. BigID enables “collective data stewardship”.
For more information, visit our website at https://www.bigid.com
Previous posts in this series: #1 Data is a Strategic Asset